3 papers
quant-ph2024
Training-efficient density quantum machine learning
Brian Coyle, Snehal Raj, Natansh Mathur +4
Quantum machine learning (QML) requires powerful, flexible and efficiently trainable models to be successful in solving challenging problems. We introduce density quantum neural ne…
q-fin.ST2023
Improved Financial Forecasting via Quantum Machine Learning
Sohum Thakkar, Skander Kazdaghli, Natansh Mathur +3
Quantum algorithms have the potential to enhance machine learning across a variety of domains and applications. In this work, we show how quantum machine learning can be used to im…
quant-ph2023
Improved clinical data imputation via classical and quantum determinantal point processes
Skander Kazdaghli, Iordanis Kerenidis, Jens Kieckbusch +1
Imputing data is a critical issue for machine learning practitioners, including in the life sciences domain, where missing clinical data is a typical situation and the reliability…